Publicaciones en las que colabora con FRANCISCO MANUEL ORTUÑO GUZMÁN (13)

2015

  1. A hierarchical classification for the selection of the most suitable multiple sequence alignment methodology

    Current Bioinformatics, Vol. 10, Núm. 2, pp. 199-207

  2. Comparing different machine learning and mathematical regression models to evaluate multiple sequence alignments

    Neurocomputing, Vol. 164, pp. 123-136

2014

  1. Creation of a database including a set of biological features related to protein sequences and their corresponding alignment

    Proceedings - IEEE Symposium on Computer-Based Medical Systems

2013

  1. Advanced classification and prediction of middle cognitive impairment to Alzheimer's disease using multi-source features

    Proceedings of the IADIS International Conference Intelligent Systems and Agents 2013, ISA 2013, Proceedings of the IADIS European Conference on Data Mining 2013, ECDM 2013

  2. An effective, practical and low computational cost framework for the integration of heterogeneous data to predict functional associations between proteins by means of artificial neural networks

    Neurocomputing, Vol. 121, pp. 64-78

  3. Comparison of different computational intelligent classifier to autonomously detect cardiac pathologies diagnosed by ECG

    International Conference on Intelligent Systems Design and Applications, ISDA

  4. Evaluating multiple sequence alignments using a LS-SVM approach with a heterogeneous set of biological features

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  5. Intelligent systems to autonomously classify several arrhythmia using information from ECG

    Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013

  6. Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: Structural information, non-gaps percentage and totally conserved columns

    Bioinformatics, Vol. 29, Núm. 17, pp. 2112-2121

  7. Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques

    Nucleic Acids Research, Vol. 41, Núm. 1

2012

  1. Optimization of multiple sequence alignment methodologies using a multiobjective evolutionary algorithm based on NSGA-II

    2012 IEEE Congress on Evolutionary Computation, CEC 2012

2011

  1. Prediction of functional associations between proteins by means of a cost-sensitive artificial neural network

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Using machine learning techniques and genomic/proteomic information from known databases for PPI prediction

    Advances in Intelligent and Soft Computing